Alarm systems, such as fire alarm systems, typically include a plurality of notification appliances (e.g. horn/strobe units), that are installed throughout a monitored building and are configured to be activated upon the detection of an alarm condition, such as the presence of fire or smoke. Occupants of the building may thereby be notified of a potentially hazardous condition and may evacuate the building or take other action before being harmed. It is therefore critically important that notification appliances of alarm systems always be in good working order.
Governmental entities may require that notification appliances, and particularly those of fire alarm systems, be tested periodically to verify that such appliances are operating properly. Such testing is typically performed by one or more designated inspectors who walk through an entire monitored building and physically visit each notification appliance installed therein. The inspectors may activate each appliance for a predetermined amount of time to verify functionality.
One shortcoming associated with traditional notification appliance testing methods is that they require inspectors to manually record test results, such as whether a particular appliance passed or failed testing. This is generally accomplished by noting test results on a piece of paper or by entering test results into an arbitrary electronic device (e.g. laptop, tablet, personal data assistant, etc.). Such manual notation can be extremely time consuming and cumbersome, especially in systems having hundreds or thousands of notification appliances.
A further shortcoming associated with traditional testing methods is that, when noting test results, inspectors must unambiguously identify each appliance that is tested. This can be surprisingly difficult, since appliance differentiation within a large group of nearly identical appliances in a building requires complex descriptions of appliances' locations and/or tedious notation of appliances' serial and device numbers. In addition to being arduous, such manual identification is susceptible to a certain level of inconsistency that is naturally attendant with any complex, manual task of this type.